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Content Based Image Retrieval for Medical Images Techniques and Storage Methods-Review Paper

International Journal of Computer Applications
© 2010 by IJCA Journal
Number 19 - Article 19
Year of Publication: 2010
Prof. K.Wanjale
Tejas Borawake
Shashideep Chaudhari

K.Wanjale, Tejas Borawake and Shashideep Chaudhari. Article: Content Based Image Retrieval for Medical Images Techniques and Storage Methods-Review Paper. International Journal of Computer Applications 1(1):105–107, February 2010. Published By Foundation of Computer Science. BibTeX

	author = {K.Wanjale and Tejas Borawake and Shashideep Chaudhari},
	title = {Article: Content Based Image Retrieval for Medical Images Techniques and Storage Methods-Review Paper},
	journal = {International Journal of Computer Applications},
	year = {2010},
	volume = {1},
	number = {1},
	pages = {105--107},
	month = {February},
	note = {Published By Foundation of Computer Science}


In the medical field, images, and especially digital images, are produced in ever increasing quantities and used for diagnostics and therapy. Content based access to medical images for supporting clinical decision making has been proposed that would ease the management of clinical data and scenarios for the integration of content-based access methods into Picture Archiving and Communication Systems (PACS) have been created.

This article gives an overview of available literature in the field of content based access to medical image data and on the technologies used in the field. Section 1 gives an introduction into generic content based image retrieval and the technologies used. Section 2 describes the basic algorithm used in the implemented systems. Section 3 describes various methods of implementing CBIR. New research directions are being defied that can prove to be useful.

This article also identifies explanations to some of the outlined problems in the field as it looks like many propositions for systems are made from the medical domain and research prototypes are developed in computer science departments using medical datasets. Still, there are very few systems that seem to be used in clinical practice.

Content-Based Image Retrieval (CBIR) has been a topic of research interest for nearly a decade. Approaches to date use image features for describing content. A survey of the literature shows that progress has been limited to prototype systems that make gross assumptions and approximations.


    [1]. Content-based Retrieval of Medical Images by Continuous Feature Selection Pedro H. Bugatti, Marcela X. Ribeiro, Agma J. M. Traina, Caetano Traina Jr Department of Computer Science - ICMC, University of Sao Paulo at Sao Carlos - USP.
    [2]. Enriching content-based medical image retrieval with automatically extracted MeSH-terms by Müller H, Ruch P, Geissbuhler A.
    [3]. Content-Based Medical Image Retrieval Using Low-Level Visual Features and Modality Identification by Juan C. Caicedo, Fabio A. Gonzalez and Eduardo Romero.
    [4]. Features for Image Retrieval: A Quantitative Comparison by Thomas Deselaers, Daniel Keysers, and Hermann Ney.
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    [6]. Image Retrieval: Ideas, Influences, and Trends of the New Age Ritendra Datta, Dhiraj Joshi, Jia Li, and James Z. Wang. The Pennsylvania State University.
    [7]. A Review of Content-Based Image Retrieval Systems in Medical Applications - Clinical Benefits and Future Directions Henning Miller, Nicolas Michoux, David Bandon and Antoine Geissbuhler Division for Medical Informatics, University Hospital of Geneva Rue Micheli-du-Crest 21, 1211 Geneva 14, Switzerland.
    [8]. A Universal Model for Content-Based Image Retrieval S. Nandagopalan, Dr. B. S. Adiga, and N. Deepak.